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We present different methods to increase the performance of Hybrid Monte Carlo simulations of the Hubbard model in two-dimensions. Our simulations concentrate on a hexagonal lattice, though can be easily generalized to other lattices. It is…

Strongly Correlated Electrons · Physics 2019-01-16 Stefan Krieg , Thomas Luu , Johann Ostmeyer , Philippos Papaphilippou , Carsten Urbach

Magnetic resonance (MR)-$T_2^*$ mapping is widely used to study hemorrhage, calcification and iron deposition in various clinical applications, it provides a direct and precise mapping of desired contrast in the tissue. However, the long…

Image and Video Processing · Electrical Eng. & Systems 2020-08-06 Shuai Huang , James J. Lah , Jason W. Allen , Deqiang Qiu

Recent developments for mathematical modeling and numerical simulation of biomolecular systems raise new demands for qualified, stable, and efficient surface meshing, especially in implicit-solvent modeling. In our former work, we have…

Numerical Analysis · Mathematics 2016-11-11 Tiantian Liu , Minxin Chen , Benzhuo Lu

We apply a method recently introduced to the statistical literature to directly estimate the precision matrix from an ensemble of samples drawn from a corresponding Gaussian distribution. Motivated by the observation that cosmological…

Instrumentation and Methods for Astrophysics · Physics 2016-05-25 Nikhil Padmanabhan , Martin White , Harrison H. Zhou , Ross O'Connell

A model-based reconstruction technique for accelerated T2 mapping with improved accuracy is proposed using undersampled Cartesian spin-echo MRI data. The technique employs an advanced signal model for T2 relaxation that accounts for…

Medical Physics · Physics 2015-03-03 Tilman J. Sumpf , Andreas Petrovic , Martin Uecker , Florian Knoll , Jens Frahm

We present a new parallel algorithm for solving triangular systems with multiple right hand sides (TRSM). TRSM is used extensively in numerical linear algebra computations, both to solve triangular linear systems of equations as well as to…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-23 Tobias Wicky , Edgar Solomonik , Torsten Hoefler

Distributed-memory matrix multiplication (MM) is a key element of algorithms in many domains (machine learning, quantum physics). Conventional algorithms for dense MM rely on regular/uniform data decomposition to ensure load balance. These…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-04-21 Justus A. Calvin , Edward F. Valeev

We introduce the tracer mass estimator. This is a new and simple way to estimate the enclosed mass from the projected positions and line of sight velocities of a tracer population (such as globular clusters, halo stars and planetary…

Astrophysics · Physics 2011-03-10 N. W. Evans , M. I. Wilkinson , K. M. Perrett , T. Bridges

We solve tensor balancing, rescaling an Nth order nonnegative tensor by multiplying N tensors of order N - 1 so that every fiber sums to one. This generalizes a fundamental process of matrix balancing used to compare matrices in a wide…

Methodology · Statistics 2018-10-30 Mahito Sugiyama , Hiroyuki Nakahara , Koji Tsuda

We study theoretical and experimental facets of mass determination of new particle states. Assuming supersymmetry, we update the quark and lepton mass matrices at the grand unification scale accounting for threshold corrections enhanced by…

High Energy Physics - Phenomenology · Physics 2009-05-12 Mario Serna

In many applications data are measured or defined on a spherical manifold; spherical harmonic transforms are then required to access the frequency content of the data. We derive algorithms to perform forward and inverse spin spherical…

Astrophysics · Physics 2011-10-28 J. D. McEwen

Many robotic tasks, such as inverse kinematics, motion planning, and optimal control, can be formulated as optimization problems. Solving these problems involves addressing nonlinear kinematics, complex contact dynamics, long-horizon…

Robotics · Computer Science 2025-09-10 Teng Xue , Yan Zhang , Amirreza Razmjoo , Sylvain Calinon

Our main objective in this paper is to develop a second-order stochastic numerical method which generalizes the well-known deterministic TR-BDF2 scheme. Since most stochastic techniques used for approximating the solution of a stochastic…

Numerical Analysis · Mathematics 2026-02-12 Tomás Caraballo , Macarena Gómez-Mármol , Ignacio Roldán

In this paper, we discuss the acceleration of the regularized alternating least square (RALS) algorithm for tensor approximation. We propose a fast iterative method using a Aitken-Stefensen like updates for the regularized algorithm.…

Numerical Analysis · Mathematics 2017-07-25 Xiaofei Wang , Carmeliza Navasca , Stefan Kindermann

We extend the geometrical inverse approximation approach for solving linear least-squares problems. For that we focus on the minimization of $1-\cos(X(A^TA),I)$, where $A$ is a given rectangular coefficient matrix and $X$ is the approximate…

Numerical Analysis · Mathematics 2019-02-25 Jean-Paul Chehab , Marcos Raydan

A new robust algorithm for the numerical computation of biarcs, i.e. $G^1$ curves composed of two arcs of circle, is presented. Many algorithms exist but are based on geometric constructions, which must consider many geometrical…

Numerical Analysis · Mathematics 2017-11-06 Enrico Bertolazzi , Marco Frego

We propose three fast algorithms for solving the inverse problem of the thermoacoustic tomography corresponding to certain acquisition geometries. Two of these methods are designed to process the measurements done with point-like detectors…

Analysis of PDEs · Mathematics 2011-02-08 Leonid Kunyansky

We describe a simple, efficient, robust and fully automatic algorithm for the determination of a Multi-Gaussian Expansion (MGE) fit to galaxy images, to be used as a parametrization for the galaxy stellar surface brightness. In most cases…

Astrophysics · Physics 2011-07-18 Michele Cappellari

A concise analytical formula is developed for the inverse of an invertible 3 x 3 matrix using a telescoping method, and is generalized to larger square matrices. The formula is confirmed using randomly generated matrices in Matlab

General Mathematics · Mathematics 2021-09-14 W Astar

In this paper, we propose a new stochastic alternating direction method of multipliers (ADMM) algorithm, which incrementally approximates the full gradient in the linearized ADMM formulation. Besides having a low per-iteration complexity as…

Machine Learning · Computer Science 2013-08-19 Leon Wenliang Zhong , James T. Kwok
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